Triple
T4578462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O.P. |
E101795
|
entity |
| Predicate | hasMeaningType |
P29818
|
FINISHED |
| Object | internet slang |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: internet slang | Statement: [O.P., hasMeaningType, internet slang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningType Context triple: [O.P., hasMeaningType, internet slang]
-
A.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
B.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
C.
hasSense
chosen
Indicates that an entity possesses or is associated with a particular sensory perception, meaning, or interpretation.
-
D.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
E.
hasConnotation
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd58e2a1808190be4582d5b3003d6c |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:10 p.m.